Poor performance in Repository mapping test tool (7.0.12)

Hi,
I'm just looking for some hints for performance tuning the Mapping tool in the Repository. This is our Development machine.
Seems to be significantly worse since upgrade from sps 10 to sps 12.
Every "display queue" / recompile of the map takes almost 5 minutes.
The Java stack currently has about 4gb of heap, abap 1gb. We reallocated a large amount from abap to java which temporarily alleviated the problem (about 60% quicker), but it's back after a few days. There is currently no possibility of adding more memory.
The problem seems to be noticable primarily with the IB, hence I'm looking for any performance tuning tips that would directly affect this. I'm thinking that we need to concentrate on the Java stack. I've looked at note 894509 and SAP NetWeaver Process Integration Tuning Guide and not seen anything directly related at first glance.
I've deactivated end-to-end monitoring.
The only thing that stands out is a significant amount of activity on the disk with the sap/oracledb/oracleexec on it. It's about 9 times greater than the amount of swap. Two processes seem to be regularly at the top of CPU usage dw.sapPID_DVEBMGS14 and /usr/sap/PID/DVEBMG.
Hints and tips appreciated. As I said, hardware changes are not possible at this time.
Thanks
James.
Yes, points will be awarded where appropriate.

Are you gacing this issue only when you test the mapping in the IR or even in the runtime?
I have also noticed that mapping test in the tool in IR always take a long time, but as they never reflect the runtime mapping perfromance I have always ignored it.
A few reasons might be,
1. Low RAM on the Machine being used by you.
2. Too Many applications!
Remember you are Connecting to the server from your IR using JWS and so the resources on your machine also matter quite a bit.
If completely off track , ignore the reply.
Regards
Bhavesh

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Please have look on below few articles,
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SAP NetWeaver XI Performance Analysis - Webinar Powerpoint
https://www.sdn.sap.com/irj/sdn/go/portal/prtroot/docs/library/uuid/489f5844-0c01-0010-79be-acc3b52250fd
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Apple maps has received a poor performance rating just after introduction of the iPhone 5. I am running google maps app on the phone. Siri cannot seem to get me to a specific address. Where does the problem lie? Thanks.

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Forms and Reports: Automated Test tools - functionality AND performance

All,
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Oracle JInitiator 1.3.1.17 or later
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Edited by: Hortense Andrian on Jan 21, 2011 1:07 AM

Hi David,
We need to do performance tuning of the application by means of adopting any test tools. On refering forum,I found various tuning strategies available to tune SQL queries.But, iam more concerned on availability of any performance test tools to do more deeper tuning of application.
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SAP provides Load testing/Performance testing tool

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*Note to author of this question: I have taken the liberty of moving this to the proper thread
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Hi Swapan,
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Hope someone comes up with a nice video presentation on SAP LOADRUNNER..
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Will award maximum points.
Please help me.. by mailing any document with some sample scenerio's step by step to my mail id: [email protected].
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hi,
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michal
<a href="/people/michal.krawczyk2/blog/2005/06/28/xipi-faq-frequently-asked-questions"><b>XI / PI FAQ - Frequently Asked Questions</b></a>

Poor performance of maps

Does anyone know of any configuration parameters that are really useful when attempting to tweak the performance of the maps in OBIEE 11.1.1.5? Although I'm the only user on a virtual box with 4GB of RAM and 2 CPUs, map rendering is painfully slow. (XML posted below, working against the "A - Sample Sales" subject area). All other OBIEE performance is quite snappy. Maps ... not so much.
Any ideas?
<saw:report xmlns:saw="com.siebel.analytics.web/report/v1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlVersion="201008230" xmlns:sawx="com.siebel.analytics.web/expression/v1.1">
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<saw:columns>
<saw:column xsi:type="saw:regularColumn" columnID="c3131dd22bf3cc8ee">
<saw:columnFormula>
<sawx:expr xsi:type="sawx:sqlExpression">"Time"."T05 Per Name Year"</sawx:expr></saw:columnFormula></saw:column>
<saw:column xsi:type="saw:regularColumn" columnID="cddcbd415b4c3bdfa">
<saw:columnFormula>
<sawx:expr xsi:type="sawx:sqlExpression">"Ship To Geo Codes"."R62 Geo Ctry State Name"</sawx:expr></saw:columnFormula></saw:column>
<saw:column xsi:type="saw:regularColumn" columnID="c371b413a6d22de6a">
<saw:columnFormula>
<sawx:expr xsi:type="sawx:sqlExpression">"Products"."P4 Brand"</sawx:expr></saw:columnFormula></saw:column>
<saw:column xsi:type="saw:regularColumn" columnID="c95ae97ecd00f14f7">
<saw:columnFormula>
<sawx:expr xsi:type="sawx:sqlExpression">"Base Facts"."1- Revenue"</sawx:expr></saw:columnFormula></saw:column>
<saw:column xsi:type="saw:regularColumn" columnID="c229fa547a7d1b4cd">
<saw:columnFormula>
<sawx:expr xsi:type="sawx:sqlExpression">"Base Facts"."2- Billed Quantity"</sawx:expr></saw:columnFormula></saw:column></saw:columns>
<saw:filter>
<sawx:expr xsi:type="sawx:comparison" op="equal">
<sawx:expr xsi:type="sawx:sqlExpression">"Ship To Geo Codes"."R61 Geo Country Code"</sawx:expr>
<sawx:expr xsi:type="xsd:string">USA</sawx:expr></sawx:expr></saw:filter></saw:criteria>
<saw:views currentView="3">
<saw:view xsi:type="saw:compoundView" name="compoundView!1">
<saw:cvTable>
<saw:cvRow>
<saw:cvCell viewName="titleView!1">
<saw:displayFormat>
<saw:formatSpec/></saw:displayFormat></saw:cvCell></saw:cvRow>
<saw:cvRow>
<saw:cvCell viewName="tableView!1">
<saw:displayFormat>
<saw:formatSpec/></saw:displayFormat></saw:cvCell></saw:cvRow></saw:cvTable></saw:view>
<saw:view xsi:type="saw:titleView" name="titleView!1"/>
<saw:view xsi:type="saw:tableView" name="tableView!1">
<saw:edges>
<saw:edge axis="page" showColumnHeader="true"/>
<saw:edge axis="section"/>
<saw:edge axis="row" showColumnHeader="true">
<saw:edgeLayers>
<saw:edgeLayer type="column" columnID="c3131dd22bf3cc8ee"/>
<saw:edgeLayer type="column" columnID="cddcbd415b4c3bdfa"/>
<saw:edgeLayer type="column" columnID="c371b413a6d22de6a"/>
<saw:edgeLayer type="column" columnID="c95ae97ecd00f14f7"/>
<saw:edgeLayer type="column" columnID="c229fa547a7d1b4cd"/></saw:edgeLayers></saw:edge>
<saw:edge axis="column"/></saw:edges></saw:view>
<saw:view xsi:type="saw:mapview" name="mapview!1">
<saw:mapLayout>
<saw:splitterLayout orientation="horizontal"/></saw:mapLayout>
<saw:basemap sid="__OBIEE__MAPVIEW__TILE__OBIEE_NAVTEQ_SAMPLE__OBIEE_WORLD_MAP__~v0"/>
<saw:mapWidgets>
<saw:mapToolBar>
<saw:panTools>
<saw:panHand display="true"/></saw:panTools>
<saw:zoomTools>
<saw:zoomIn display="true"/>
<saw:zoomOut display="true"/></saw:zoomTools>
<saw:selectionTools>
<saw:pointTool display="true"/></saw:selectionTools></saw:mapToolBar>
<saw:mapInformation>
<saw:scaleInfo display="true"/>
<saw:overview display="true" viewState="collapsed"/></saw:mapInformation>
<saw:mapOverlay>
<saw:panButtons display="true"/>
<saw:zoomSlider display="true"/></saw:mapOverlay></saw:mapWidgets>
<saw:infoLegend display="true" viewState="collapsed"/>
<saw:viewportInfo>
<saw:boundingLayer layerID="l0"/>
<saw:mapCenter x="-95.90625" y="34.3125" size="31.015625" srid="8307" zoomLevel="3" xUnitPixels="12.8" yUnitPixels="12.8"/>
<saw:boundingBox coords="-119.34375,18.8828125,-72.546875,49.8203125"/></saw:viewportInfo>
<saw:spatialLayers>
<saw:spatialLayer sid="__OBIEE__MAPVIEW__LAYER__OBIEE_NAVTEQ_Sample__OBIEE_STATE__~v0" class="omv_predefined_layer" layerID="l0">
<saw:layerLabelFormat display="true"/>
<saw:spatials>
<saw:columnRef columnID="cddcbd415b4c3bdfa"/></saw:spatials>
<saw:visuals>
<saw:visual visualID="v0" xsi:type="saw:colorScheme">
<saw:varyFillColor binType="percentile" numBins="4">
<saw:columnRef columnID="c95ae97ecd00f14f7"/>
<saw:rampStyle>
<saw:rampItem id="0">
<saw:g class="color" fill="#fffeff"/></saw:rampItem>
<saw:rampItem id="1">
<saw:g class="color" fill="#eae6ec"/></saw:rampItem>
<saw:rampItem id="2">
<saw:g class="color" fill="#d2cfd5"/></saw:rampItem>
<saw:rampItem id="3">
<saw:g class="color" fill="#bcb8be"/></saw:rampItem></saw:rampStyle></saw:varyFillColor>
<saw:g class="color"/></saw:visual></saw:visuals></saw:spatialLayer></saw:spatialLayers>
<saw:canvasFormat width="800" height="400"/>
<saw:mapInteraction autoCreateFormats="true"/>
<saw:formatPanel width="218" height="513"/></saw:view></saw:views></saw:report>

Here are few tuning tips you might want to look at.
http://oraclemaps.blogspot.in/2010/01/mapviewer-performance-tuning-tips-part.html
http://oraclemaps.blogspot.in/2010/01/mapviewer-performance-tuning-tips-part_14.html
http://oraclemaps.blogspot.in/2010/02/mapviewer-performance-tuning-tips-part.html
http://oraclemaps.blogspot.in/2010/09/mapviewer-performance-tuning-tips-part.html

Poor performance of the BDB cache

I'm experiencing incredibly poor performance of the BDB cache and wanted to share my experience, in case anybody has any suggestions.
Overview
Stone Steps maintains a fork of a web log analysis tool - the Webalizer (http://www.stonesteps.ca/projects/webalizer/). One of the problems with the Webalizer is that it maintains all data (i.e. URLs, search strings, IP addresses, etc) in memory, which puts a cap on the maximum size of the data set that can be analyzed. Naturally, BDB was picked as the fastest database to maintain analyzed data on disk set and produce reports by querying the database. Unfortunately, once the database grows beyond the cache size, overall performance goes down the drain.
Note that the version of SSW available for download does not support BDB in the way described below. I can make the source available for you, however, if you find your own large log files to analyze.
The Database
Stone Steps Webalizer (SSW) is a command-line utility and needs to preserve all intermediate data for the month on disk. The original approach was to use a plain-text file (webalizer.current, for those who know anything about SSW). The BDB database that replaced this plain text file consists of the following databases:
sequences (maintains record IDs for all other tables)
urls -primary database containing URL data - record ID (key), URL itself, grouped data, such as number of hits, transfer size, etc)
urls.values - secondary database that contains a hash of the URL (key) and the record ID linking it to the primary database; this database is used for value lookups)
urls.hits - secondary database that contains the number of hits for each URL (key) and the record ID to link it to the primary database; this database is used to order URLs in the report by the number of hits.
The remaining databases are here just to indicate the database structure. They are the same in nature as the two described above. The legend is as follows: (s) will indicate a secondary database, (p) - primary database, (sf) - filtered secondary database (using DB_DONOTINDEX).
urls.xfer (s), urls.entry (s), urls.exit (s), urls.groups.hits (sf), urls.groups.xfer (sf)
hosts (p), hosts.values (s), hosts.hits (s), hosts.xfer (s), hosts.groups.hits (sf), hosts.groups.xfer (sf)
downloads (p), downloads.values (s), downloads.xfer (s)
agents (p), agents.values (s), agents.values (s), agents.hits (s), agents.visits (s), agents.groups.visits (sf)
referrers (p), referrers.values (s), referrers.values (s), referrers.hits (s), referrers.groups.hits (sf)
search (p), search.values (s), search.hits (s)
users (p), users.values (s), users.hits (s), users.groups.hits (sf)
errors (p), errors.values (s), errors.hits (s)
dhosts (p), dhosts.values (s)
statuscodes (HTTP status codes)
totals.daily (31 days)
totals.hourly (24 hours)
totals (one record)
countries (a couple of hundred countries)
system (one record)
visits.active (active visits - variable length)
downloads.active (active downloads - variable length)
All these databases (49 of them) are maintained in a single file. Maintaining a single database file is a requirement, so that the entire database for the month can be renamed, backed up and used to produce reports on demand.
Database Size
One of the sample Squid logs I received from a user contains 4.4M records and is about 800MB in size. The resulting database is 625MB in size. Note that there is no duplication of text data - only nodes and such values as hits and transfer sizes are duplicated. Each record also contains some small overhead (record version for upgrades, etc).
Here are the sizes of the URL databases (other URL secondary databases are similar to urls.hits described below):
urls (p):
8192 Underlying database page size
2031 Overflow key/data size
1471636 Number of unique keys in the tree
1471636 Number of data items in the tree
193 Number of tree internal pages
577738 Number of bytes free in tree internal pages (63% ff)
55312 Number of tree leaf pages
145M Number of bytes free in tree leaf pages (67% ff)
2620 Number of tree overflow pages
16M Number of bytes free in tree overflow pages (25% ff)
urls.hits (s)
8192 Underlying database page size
2031 Overflow key/data size
2 Number of levels in the tree
823 Number of unique keys in the tree
1471636 Number of data items in the tree
31 Number of tree internal pages
201970 Number of bytes free in tree internal pages (20% ff)
45 Number of tree leaf pages
243550 Number of bytes free in tree leaf pages (33% ff)
2814 Number of tree duplicate pages
8360024 Number of bytes free in tree duplicate pages (63% ff)
0 Number of tree overflow pages
The Testbed
I'm running all these tests using the latest BDB (v4.6) built from the source on Win2K3 server (release version). The test machine is 1.7GHz P4 with 1GB of RAM and an IDE hard drive. Not the fastest machine, but it was able to handle a log file like described before at a speed of 20K records/sec.
BDB is configured in a single file in a BDB environment, using private memory, since only one process ever has access to the database).
I ran a performance monitor while running SSW, capturing private bytes, disk read/write I/O, system cache size, etc.
I also used a code profiler to analyze SSW and BDB performance.
The Problem
Small log files, such as 100MB, can be processed in no time - BDB handles them really well. However, once the entire BDB cache is filled up, the machine goes into some weird state and can sit in this state for hours and hours before completing the analysis.
Another problem is that traversing large primary or secondary databases is a really slow and painful process. It is really not that much data!
Overall, the 20K rec/sec quoted above drop down to 2K rec/sec. And that's all after most of the analysis has been done, just trying to save the database.
The Tests
SSW runs in two modes, memory mode and database mode. In memory mode, all data is kept in memory in SSW's own hash tables and then saved to BDB at the end of each run.
In memory mode, the entire BDB is dumped to disk at the end of the run. First, it runs fairly fast, until the BDB cache is filled up. Then writing (disk I/O) goes at a snail pace, at about 3.5MB/sec, even though this disk can write at about 12-15MB/sec.
Another problem is that the OS cache gets filled up, chewing through all available memory long before completion. In order to deal with this problem, I disabled the system cache using the DB_DIRECT_DB/LOG options. I could see OS cache left alone, but once BDB cache was filed up, processing speed was as good as stopped.
Then I flipped options and used DB_DSYNC_DB/LOG options to disable OS disk buffering. This improved overall performance and even though OS cache was filling up, it was being flushed as well and, eventually, SSW finished processing this log, sporting 2K rec/sec. At least it finished, though - other combinations of these options lead to never-ending tests.
In the database mode, stale data is put into BDB after processing every N records (e.g. 300K rec). In this mode, BDB behaves similarly - until the cache is filled up, the performance is somewhat decent, but then the story repeats.
Some of the other things I tried/observed:
* I tried to experiment with the trickle option. In all honesty, I hoped that this would be the solution to my problems - trickle some, make sure it's on disk and then continue. Well, trickling was pretty much useless and didn't make any positive impact.
* I disabled threading support, which gave me some performance boost during regular value lookups throughout the test run, but it didn't help either.
* I experimented with page size, ranging them from the default 8K to 64K. Using large pages helped a bit, but as soon as the BDB cached filled up, the story repeated.
* The Db.put method, which was called 73557 times while profiling saving the database at the end, took 281 seconds. Interestingly enough, this method called ReadFile function (Win32) 20000 times, which took 258 seconds. The majority of the Db.put time was wasted on looking up records that were being updated! These lookups seem to be the true problem here.
* I tried libHoard - it usually provides better performance, even in a single-threaded process, but libHoard didn't help much in this case.

I have been able to improve processing speed up to
6-8 times with these two techniques:
1. A separate trickle thread was created that would
periodically call DbEnv::memp_trickle. This works
especially good on multicore machines, but also
speeds things up a bit on single CPU boxes. This
alone improved speed from 2K rec/sec to about 4K
rec/sec.Hello Stone,
I am facing a similar problem, and I too hope to resolve the same with memp_trickle. I had these queries.
1. what was the % of clean pages that you specified?
2. What duration were you clling this thread to call memp_trickle?
This would give me a rough idea about which to tune my app. Would really appreciate if you can answer these queries.
Regards,
Nishith.
>
2. Maintaining multiple secondary databases in real
time proved to be the bottleneck. The code was
changed to create secondary databases at the end of
the run (calling Db::associate with the DB_CREATE
flag), right before the reports are generated, which
use these secondary databases. This improved speed
from 4K rec/sec to 14K rec/sec.

Poor Performance in ETL SCD Load

Hi gurus,
We are facing some serious performance problems during an UPDATE step, which is part of a SCD type 2 process for Assets (SIL_Vert/SIL_AssetDimension_SCDUpdate). The source system is Siebel CRM. The tools for ETL processing are listed below:
Informatica PowerCenter 9.1.0 HotFix2 0902 357 (R181 D90)
Oracle BI Data Warehouse Administration Console (Dac Build AN 10.1.3.4.1.patch.20120711.0516)
The OOTB mapping for this step is a simple SELECT command - which retrieves historical records from the Dimension to be updated - and the Target table (W_ASSET_D), with no UPDATE Strategy. The session is configured to always perform UPDATEs. We also have set $$UDATE_ALL_HISTORY to "N" in DAC: this way we are only selecting the most recent records from the Dimension history, and the only columns that are effectively updated are the system columns of SCD (EFFECTIVE_FROM_DT, EFFECTIVE_TO_DT, CURRENT_FLG, ...).
The problem is that the UPDATE command is executed individually by Informatica Powercenter, for each record in W_ASSET_D. For a number of 2.486.000 UPDATEs, we had ~2h of processing - a very poor performance for only one ETL step. Our W_ASSET_D has ~150M records today.
Some questions for the above:
- is this an expected average execution duration for this number of records?
- updates record by record are not optimal, this could be easily overcome by a BULK COLLECT/FORALL method. Is there a way to optimize the method used by Informatica or we need to write our own PL-SQL script and run it in DAC?
Thanks in advance,
Guilherme

Hi,
Thank you for posting in Windows Server Forum.
Initially please check the configuration & requirement part for RemoteFX. You can follow below article for further research.
RemoteFX vGPU Setup and Configuration Guide for Windows Server 2012
http://social.technet.microsoft.com/wiki/contents/articles/16652.remotefx-vgpu-setup-and-configuration-guide-for-windows-server-2012.aspx
Hope it helps!
Thanks.
Dharmesh Solanki
TechNet Community Support

Is it possible to use external testing tools in SAP XI

Hi,
I have been working on file to file transfer of large size more than 1 GB. I have many doubts like:
1.Can I use Data compression techniques so that my files can be processsed(my scenario involves a lot of mapping)
2.Can any of the engines be stopped so that processing speed increases.
3.Can any of the third party testing tools like Load runner be used in to monitor the process.
Please help me with sloutions.
Thanks in advance.

One GB is a very huge file. First of all check ur XI hardware configuration.
1. U may write ur adapter module to zip the message.
2. It wont affect the performance much if the file size is 1 GB. Also u cant stop adapter engine (File Adapter) and the Integration Engine in ur scenario
3. U can do the load testing on XI using load runner
Regards,
Prateek

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